TranSeVis: A visual analytics system for transportation data sensing and exploration

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Abstract

With increasing availability of location-acquisition technologies, huge volumes of data tracking transportation system have been collected. These data are highly valuable for unveiling human mobility patterns, transportation system utilization, and urban planning. However, it is still highly challenging to visualize and explore transportation data. In this paper, an interactive visual analytic system, TranSeVis has been proposed. It has two visualization modules, one named region view provides geographical information and effective temporal information comparison, the other named road view provides detailed visual analysis of mobility factors along routes or congestions spots. Besides, two case studies have been used to evaluate the visualization techniques and real-world taxi data sets have been used to demonstrate TranSeVis. Based on the results, TranSeVis offers transportation researchers an easy-to-use, efficient, and scalable platform to visualize and explore transportation data.

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APA

Gong, R., Teng, Z., Han, M., Wei, L., Zhang, Y., & Pu, J. (2018). TranSeVis: A visual analytics system for transportation data sensing and exploration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11151 LNCS, pp. 1–10). Springer Verlag. https://doi.org/10.1007/978-3-030-00560-3_1

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